| Title |
PPM_One: a static protein structure based chemical shift predictor
|
|---|---|
| Published in |
Journal of Biomolecular NMR, June 2015
|
| DOI | 10.1007/s10858-015-9958-z |
| Pubmed ID | |
| Authors |
Dawei Li, Rafael Brüschweiler |
| Abstract |
We mined the most recent editions of the BioMagResDataBank and the protein data bank to parametrize a new empirical knowledge-based chemical shift predictor of protein backbone atoms using either a linear or an artificial neural network model. The resulting chemical shift predictor PPM_One accepts a single static 3D structure as input and emulates the effect of local protein dynamics via interatomic steric contacts. Furthermore, the chemical shift prediction was extended to most side-chain protons and it is found that the prediction accuracy is at a level allowing an independent assessment of stereospecific assignments. For a previously established set of test proteins some overall improvement was achieved over current top-performing chemical shift prediction programs. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Canada | 1 | 2% |
| Unknown | 42 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 30% |
| Student > Ph. D. Student | 12 | 27% |
| Student > Bachelor | 4 | 9% |
| Professor | 2 | 5% |
| Other | 2 | 5% |
| Other | 2 | 5% |
| Unknown | 9 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 11 | 25% |
| Agricultural and Biological Sciences | 8 | 18% |
| Biochemistry, Genetics and Molecular Biology | 8 | 18% |
| Computer Science | 1 | 2% |
| Earth and Planetary Sciences | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 12 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 June 2015.
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#18,417,643
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Outputs from Journal of Biomolecular NMR
#461
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#189,809
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Outputs of similar age from Journal of Biomolecular NMR
#5
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